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04/22/2023
Planning-inspired Hierarchical Trajectory Prediction for Autonomous Driving
Recently, anchor-based trajectory prediction methods have shown promisin...
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11/23/2022
Prototypical context-aware dynamics generalization for high-dimensional model-based reinforcement learning
The latent world model provides a promising way to learn policies in a c...
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10/19/2022
Conditional Goal-oriented Trajectory Prediction for Interacting Vehicles with Vectorized Representation
This paper aims to tackle the interactive behavior prediction task, and ...
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03/31/2022
TrajGen: Generating Realistic and Diverse Trajectories with Reactive and Feasible Agent Behaviors for Autonomous Driving
Realistic and diverse simulation scenarios with reactive and feasible ag...
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02/19/2022
Multi-task Safe Reinforcement Learning for Navigating Intersections in Dense Traffic
Multi-task intersection navigation including the unprotected turning lef...
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09/24/2021
MORSE-STF: A Privacy Preserving Computation System
Privacy-preserving machine learning has become a popular area of researc...
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09/22/2021
A Reinforcement Learning Benchmark for Autonomous Driving in Intersection Scenarios
In recent years, control under urban intersection scenarios becomes an e...
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09/22/2021
Benchmarking Lane-changing Decision-making for Deep Reinforcement Learning
The development of autonomous driving has attracted extensive attention ...
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09/21/2020
Dynamic Horizon Value Estimation for Model-based Reinforcement Learning
Existing model-based value expansion methods typically leverage a world ...
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07/23/2020
Deep Reinforcement Learning based Automatic Exploration for Navigation in Unknown Environment
This paper investigates the automatic exploration problem under the unkn...
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04/18/2020
BiFNet: Bidirectional Fusion Network for Road Segmentation
Multi-sensor fusion-based road segmentation plays an important role in t...
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03/30/2019
Lane Change Decision-making through Deep Reinforcement Learning with Rule-based Constraints
Autonomous driving decision-making is a great challenge due to the compl...
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10/30/2018
